Overview

Brought to you by YData

Dataset statistics

Number of variables19
Number of observations17564
Missing cells87540
Missing cells (%)26.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory152.0 B

Variable types

Text13
Categorical1
Numeric3
DateTime2

Alerts

소재지도로명주소 has 14132 (80.5%) missing valuesMissing
소재지지번주소 has 227 (1.3%) missing valuesMissing
공원보유시설(운동시설) has 12410 (70.7%) missing valuesMissing
공원보유시설(유희시설) has 11152 (63.5%) missing valuesMissing
공원보유시설(편익시설) has 12511 (71.2%) missing valuesMissing
공원보유시설(교양시설) has 16932 (96.4%) missing valuesMissing
공원보유시설(기타시설) has 14850 (84.5%) missing valuesMissing
지정고시일 has 3172 (18.1%) missing valuesMissing
관리기관명 has 1029 (5.9%) missing valuesMissing
전화번호 has 1125 (6.4%) missing valuesMissing
공원면적 is highly skewed (γ1 = 22.96162162)Skewed

Reproduction

Analysis started2024-08-13 16:00:22.854082
Analysis finished2024-08-13 16:00:25.689861
Duration2.84 seconds
Software versionydata-profiling vv4.9.0
Download configurationconfig.json

Variables

관리번호
Text

Distinct16637
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:25.826251image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters193204
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15800 ?
Unique (%)90.0%

Sample

1st row41830-00017
2nd row41830-00031
3rd row41830-00018
4th row41830-00019
5th row41830-00020
ValueCountFrequency (%)
42780-00000 22
 
0.1%
44770-25321 14
 
0.1%
44770-25028 10
 
0.1%
42760-00024 5
 
< 0.1%
41830-00029 5
 
< 0.1%
44133-00067 4
 
< 0.1%
44131-00025 4
 
< 0.1%
44131-00024 4
 
< 0.1%
26260-00025 4
 
< 0.1%
44133-00068 4
 
< 0.1%
Other values (16627) 17488
99.6%
2024-08-14T01:00:26.060690image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 69115
35.8%
1 28075
14.5%
4 18329
 
9.5%
- 17564
 
9.1%
2 14243
 
7.4%
3 10919
 
5.7%
5 8723
 
4.5%
7 8278
 
4.3%
6 6555
 
3.4%
8 6516
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 193204
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 69115
35.8%
1 28075
14.5%
4 18329
 
9.5%
- 17564
 
9.1%
2 14243
 
7.4%
3 10919
 
5.7%
5 8723
 
4.5%
7 8278
 
4.3%
6 6555
 
3.4%
8 6516
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 193204
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 69115
35.8%
1 28075
14.5%
4 18329
 
9.5%
- 17564
 
9.1%
2 14243
 
7.4%
3 10919
 
5.7%
5 8723
 
4.5%
7 8278
 
4.3%
6 6555
 
3.4%
8 6516
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 193204
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 69115
35.8%
1 28075
14.5%
4 18329
 
9.5%
- 17564
 
9.1%
2 14243
 
7.4%
3 10919
 
5.7%
5 8723
 
4.5%
7 8278
 
4.3%
6 6555
 
3.4%
8 6516
 
3.4%

공원명
Text

Distinct14296
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:26.302163image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length28
Median length25
Mean length6.4498975
Min length1

Characters and Unicode

Total characters113286
Distinct characters809
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12457 ?
Unique (%)70.9%

Sample

1st row광탄2호 소공원
2nd row광탄3호 소공원
3rd row공흥 소공원
4th row한강아트로드 공원
5th row강하 소공원
ValueCountFrequency (%)
어린이공원 532
 
2.5%
소공원 457
 
2.1%
공원 294
 
1.4%
근린공원 221
 
1.0%
1호 103
 
0.5%
2호 81
 
0.4%
마을쉼터 72
 
0.3%
3호 57
 
0.3%
문화공원 53
 
0.2%
수변공원 52
 
0.2%
Other values (13890) 19440
91.0%
2024-08-14T01:00:26.689474image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 13985
 
12.3%
공 13957
 
12.3%
린 3979
 
3.5%
3938
 
3.5%
이 3277
 
2.9%
1 3087
 
2.7%
어 2933
 
2.6%
호 2772
 
2.4%
( 2186
 
1.9%
) 2183
 
1.9%
Other values (799) 60989
53.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 113286
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
원 13985
 
12.3%
공 13957
 
12.3%
린 3979
 
3.5%
3938
 
3.5%
이 3277
 
2.9%
1 3087
 
2.7%
어 2933
 
2.6%
호 2772
 
2.4%
( 2186
 
1.9%
) 2183
 
1.9%
Other values (799) 60989
53.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 113286
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
원 13985
 
12.3%
공 13957
 
12.3%
린 3979
 
3.5%
3938
 
3.5%
이 3277
 
2.9%
1 3087
 
2.7%
어 2933
 
2.6%
호 2772
 
2.4%
( 2186
 
1.9%
) 2183
 
1.9%
Other values (799) 60989
53.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 113286
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
원 13985
 
12.3%
공 13957
 
12.3%
린 3979
 
3.5%
3938
 
3.5%
이 3277
 
2.9%
1 3087
 
2.7%
어 2933
 
2.6%
호 2772
 
2.4%
( 2186
 
1.9%
) 2183
 
1.9%
Other values (799) 60989
53.8%

공원구분
Categorical

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size137.3 KiB
어린이공원
8934 
근린공원
3898 
소공원
2808 
문화공원
 
434
기타
 
413
Other values (12)
1077 

Length

Max length8
Median length5
Mean length4.3425188
Min length2

Characters and Unicode

Total characters76272
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row소공원
2nd row소공원
3rd row소공원
4th row소공원
5th row소공원

Common Values

ValueCountFrequency (%)
어린이공원 8934
50.9%
근린공원 3898
22.2%
소공원 2808
 
16.0%
문화공원 434
 
2.5%
기타 413
 
2.4%
수변공원 354
 
2.0%
체육공원 256
 
1.5%
역사공원 186
 
1.1%
기타(공공공지) 139
 
0.8%
기타(광장) 48
 
0.3%
Other values (7) 94
 
0.5%

Length

2024-08-14T01:00:26.767475image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이공원 8934
50.9%
근린공원 3898
22.2%
소공원 2808
 
16.0%
문화공원 434
 
2.5%
기타 413
 
2.4%
수변공원 354
 
2.0%
체육공원 256
 
1.5%
역사공원 186
 
1.1%
기타(공공공지 139
 
0.8%
기타(광장 48
 
0.3%
Other values (7) 94
 
0.5%

Most occurring characters

ValueCountFrequency (%)
공 17375
22.8%
원 16958
22.2%
린 12832
16.8%
어 8934
11.7%
이 8934
11.7%
근 3898
 
5.1%
소 2808
 
3.7%
기 644
 
0.8%
타 644
 
0.8%
문 434
 
0.6%
Other values (24) 2811
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 76272
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
공 17375
22.8%
원 16958
22.2%
린 12832
16.8%
어 8934
11.7%
이 8934
11.7%
근 3898
 
5.1%
소 2808
 
3.7%
기 644
 
0.8%
타 644
 
0.8%
문 434
 
0.6%
Other values (24) 2811
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 76272
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
공 17375
22.8%
원 16958
22.2%
린 12832
16.8%
어 8934
11.7%
이 8934
11.7%
근 3898
 
5.1%
소 2808
 
3.7%
기 644
 
0.8%
타 644
 
0.8%
문 434
 
0.6%
Other values (24) 2811
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 76272
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
공 17375
22.8%
원 16958
22.2%
린 12832
16.8%
어 8934
11.7%
이 8934
11.7%
근 3898
 
5.1%
소 2808
 
3.7%
기 644
 
0.8%
타 644
 
0.8%
문 434
 
0.6%
Other values (24) 2811
 
3.7%

소재지도로명주소
Text

MISSING 

Distinct3306
Distinct (%)96.3%
Missing14132
Missing (%)80.5%
Memory size137.3 KiB
2024-08-14T01:00:26.960800image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length41
Median length36
Mean length20.857809
Min length1

Characters and Unicode

Total characters71584
Distinct characters438
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3232 ?
Unique (%)94.2%

Sample

1st row경기도 양평군 강하면 운심길 58
2nd row경기도 양평군 양평읍 오빈1리길12번길 4
3rd row경기도 양평군 양평읍 오빈1리길 9
4th row대구광역시 달서구 학산로2길 38
5th row대구광역시 달서구 앞산순환로 255
ValueCountFrequency (%)
경기도 902
 
5.9%
서울특별시 432
 
2.8%
대구광역시 255
 
1.7%
경상남도 219
 
1.4%
전북특별자치도 218
 
1.4%
달서구 183
 
1.2%
부산광역시 180
 
1.2%
노원구 175
 
1.1%
경상북도 155
 
1.0%
제주특별자치도 149
 
1.0%
Other values (4774) 12396
81.2%
2024-08-14T01:00:27.263571image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11832
 
16.5%
시 3162
 
4.4%
로 2676
 
3.7%
1 2583
 
3.6%
구 2283
 
3.2%
도 2120
 
3.0%
길 2059
 
2.9%
2 1852
 
2.6%
3 1447
 
2.0%
경 1377
 
1.9%
Other values (428) 40193
56.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 71584
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
11832
 
16.5%
시 3162
 
4.4%
로 2676
 
3.7%
1 2583
 
3.6%
구 2283
 
3.2%
도 2120
 
3.0%
길 2059
 
2.9%
2 1852
 
2.6%
3 1447
 
2.0%
경 1377
 
1.9%
Other values (428) 40193
56.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 71584
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
11832
 
16.5%
시 3162
 
4.4%
로 2676
 
3.7%
1 2583
 
3.6%
구 2283
 
3.2%
도 2120
 
3.0%
길 2059
 
2.9%
2 1852
 
2.6%
3 1447
 
2.0%
경 1377
 
1.9%
Other values (428) 40193
56.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 71584
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
11832
 
16.5%
시 3162
 
4.4%
로 2676
 
3.7%
1 2583
 
3.6%
구 2283
 
3.2%
도 2120
 
3.0%
길 2059
 
2.9%
2 1852
 
2.6%
3 1447
 
2.0%
경 1377
 
1.9%
Other values (428) 40193
56.1%

소재지지번주소
Text

MISSING 

Distinct16521
Distinct (%)95.3%
Missing227
Missing (%)1.3%
Memory size137.3 KiB
2024-08-14T01:00:27.488855image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length46
Median length42
Mean length19.585049
Min length13

Characters and Unicode

Total characters339546
Distinct characters372
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15747 ?
Unique (%)90.8%

Sample

1st row경기도 양평군 용문면 광탄리 711
2nd row경기도 양평군 용문면 광탄리 762
3rd row경기도 양평군 양평읍 공흥리 885-1
4th row경기도 양평군 강하면 운심리 43-25
5th row경기도 양평군 강하면 운심리 28-1
ValueCountFrequency (%)
경기도 4512
 
5.9%
서울특별시 1902
 
2.5%
충청남도 1720
 
2.2%
경상남도 1239
 
1.6%
전라남도 998
 
1.3%
경상북도 980
 
1.3%
충청북도 788
 
1.0%
인천광역시 744
 
1.0%
부산광역시 705
 
0.9%
대구광역시 654
 
0.8%
Other values (13887) 62819
81.5%
2024-08-14T01:00:27.792629image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59859
 
17.6%
시 15870
 
4.7%
동 14777
 
4.4%
1 14093
 
4.2%
도 12412
 
3.7%
구 9804
 
2.9%
- 9800
 
2.9%
2 7935
 
2.3%
경 7082
 
2.1%
3 6834
 
2.0%
Other values (362) 181080
53.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 339546
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
59859
 
17.6%
시 15870
 
4.7%
동 14777
 
4.4%
1 14093
 
4.2%
도 12412
 
3.7%
구 9804
 
2.9%
- 9800
 
2.9%
2 7935
 
2.3%
경 7082
 
2.1%
3 6834
 
2.0%
Other values (362) 181080
53.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 339546
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
59859
 
17.6%
시 15870
 
4.7%
동 14777
 
4.4%
1 14093
 
4.2%
도 12412
 
3.7%
구 9804
 
2.9%
- 9800
 
2.9%
2 7935
 
2.3%
경 7082
 
2.1%
3 6834
 
2.0%
Other values (362) 181080
53.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 339546
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
59859
 
17.6%
시 15870
 
4.7%
동 14777
 
4.4%
1 14093
 
4.2%
도 12412
 
3.7%
구 9804
 
2.9%
- 9800
 
2.9%
2 7935
 
2.3%
경 7082
 
2.1%
3 6834
 
2.0%
Other values (362) 181080
53.3%

위도
Real number (ℝ)

Distinct17041
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.537278
Minimum31.373335
Maximum38.49317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:27.873752image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum31.373335
5-th percentile34.942846
Q135.771576
median36.810368
Q337.454903
95-th percentile37.708614
Maximum38.49317
Range7.1198345
Interquartile range (IQR)1.683327

Descriptive statistics

Standard deviation1.0255441
Coefficient of variation (CV)0.028068432
Kurtosis-0.39342644
Mean36.537278
Median Absolute Deviation (MAD)0.73154676
Skewness-0.65434957
Sum641740.75
Variance1.0517407
MonotonicityNot monotonic
2024-08-14T01:00:27.949896image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.024696 11
 
0.1%
35.3368852 11
 
0.1%
37.385549 10
 
0.1%
35.339239 10
 
0.1%
35.8769132 8
 
< 0.1%
35.185835 7
 
< 0.1%
34.9527678 5
 
< 0.1%
37.322585 5
 
< 0.1%
37.20156456 5
 
< 0.1%
35.158055 4
 
< 0.1%
Other values (17031) 17488
99.6%
ValueCountFrequency (%)
31.373335 1
< 0.1%
33.218571 1
< 0.1%
33.229983 1
< 0.1%
33.2368203 1
< 0.1%
33.243482 1
< 0.1%
33.243883 1
< 0.1%
33.244971 1
< 0.1%
33.245738 1
< 0.1%
33.246128 1
< 0.1%
33.246941 1
< 0.1%
ValueCountFrequency (%)
38.49316951 1
< 0.1%
38.46620019 1
< 0.1%
38.44888694 1
< 0.1%
38.44514179 1
< 0.1%
38.43808083 1
< 0.1%
38.42863272 1
< 0.1%
38.39830146 1
< 0.1%
38.39408075 1
< 0.1%
38.39400595 1
< 0.1%
38.38585113 1
< 0.1%

경도
Real number (ℝ)

Distinct17015
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.46718
Minimum125.43301
Maximum137.20266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:28.030287image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum125.43301
5-th percentile126.58807
Q1126.87296
median127.10329
Q3128.06798
95-th percentile129.1665
Maximum137.20266
Range11.769649
Interquartile range (IQR)1.1950248

Descriptive statistics

Standard deviation0.84464408
Coefficient of variation (CV)0.006626365
Kurtosis0.65356168
Mean127.46718
Median Absolute Deviation (MAD)0.3328
Skewness1.0572468
Sum2238833.6
Variance0.71342362
MonotonicityNot monotonic
2024-08-14T01:00:28.109296image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.913794 11
 
0.1%
129.1613769 11
 
0.1%
129.1774978 10
 
0.1%
126.953689 10
 
0.1%
127.114948 9
 
0.1%
128.564447 7
 
< 0.1%
127.1152247 5
 
< 0.1%
127.6935954 5
 
< 0.1%
126.676651 4
 
< 0.1%
126.806747 4
 
< 0.1%
Other values (17005) 17488
99.6%
ValueCountFrequency (%)
125.4330115 1
< 0.1%
126.029652 1
< 0.1%
126.0534382 1
< 0.1%
126.0731988 1
< 0.1%
126.1218957 1
< 0.1%
126.1636958 1
< 0.1%
126.1658164 1
< 0.1%
126.1817498 1
< 0.1%
126.183145 1
< 0.1%
126.1851594 1
< 0.1%
ValueCountFrequency (%)
137.202661 1
< 0.1%
130.9059539 1
< 0.1%
130.8997121 1
< 0.1%
130.8884622 1
< 0.1%
130.8759026 1
< 0.1%
130.8718627 1
< 0.1%
130.8703392 1
< 0.1%
130.857851 1
< 0.1%
130.8556888 1
< 0.1%
130.8386897 1
< 0.1%

공원면적
Real number (ℝ)

SKEWED 

Distinct11249
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31042.725
Minimum0
Maximum9320660
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:28.186441image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile460
Q11501.225
median2240.9
Q310263.25
95-th percentile102105.55
Maximum9320660
Range9320660
Interquartile range (IQR)8762.025

Descriptive statistics

Standard deviation202048.66
Coefficient of variation (CV)6.5087283
Kurtosis756.5551
Mean31042.725
Median Absolute Deviation (MAD)1275.45
Skewness22.961622
Sum5.4523443 × 108
Variance4.0823663 × 1010
MonotonicityNot monotonic
2024-08-14T01:00:28.263575image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500 580
 
3.3%
1600 58
 
0.3%
2000 56
 
0.3%
1501 55
 
0.3%
1500.1 55
 
0.3%
1500.2 39
 
0.2%
1503 36
 
0.2%
1502 33
 
0.2%
1653 31
 
0.2%
1650 30
 
0.2%
Other values (11239) 16591
94.5%
ValueCountFrequency (%)
0 3
< 0.1%
1.535 1
 
< 0.1%
2.639 1
 
< 0.1%
3.411 1
 
< 0.1%
22 1
 
< 0.1%
30 1
 
< 0.1%
33 1
 
< 0.1%
33.003 1
 
< 0.1%
39 2
< 0.1%
41 2
< 0.1%
ValueCountFrequency (%)
9320660 1
< 0.1%
8703000 1
< 0.1%
7404000 1
< 0.1%
6691885.3 1
< 0.1%
5608490 1
< 0.1%
5332422 1
< 0.1%
3994734 1
< 0.1%
3721692.4 1
< 0.1%
3699833 1
< 0.1%
3694058 1
< 0.1%

공원보유시설(운동시설)
Text

MISSING 

Distinct2013
Distinct (%)39.1%
Missing12410
Missing (%)70.7%
Memory size137.3 KiB
2024-08-14T01:00:28.438255image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length250
Median length126
Mean length11.973419
Min length1

Characters and Unicode

Total characters61711
Distinct characters416
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1638 ?
Unique (%)31.8%

Sample

1st row농구장+축구장+테니스장
2nd row마라톤운동기+윗몸일으키기
3rd row운동기구 4종
4th row운동기구 4종
5th row운동기구 4종
ValueCountFrequency (%)
운동기구 580
 
8.6%
등 443
 
6.6%
체력단련시설 438
 
6.5%
농구장 293
 
4.3%
야외운동기구 286
 
4.2%
배드민턴장 191
 
2.8%
공중걷기 141
 
2.1%
허리돌리기 109
 
1.6%
외 76
 
1.1%
게이트볼장 73
 
1.1%
Other values (1981) 4131
61.1%
2024-08-14T01:00:28.716914image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 4915
 
8.0%
+ 4868
 
7.9%
구 3381
 
5.5%
장 2935
 
4.8%
동 2028
 
3.3%
운 2012
 
3.3%
리 1836
 
3.0%
1610
 
2.6%
1 1316
 
2.1%
체 1133
 
1.8%
Other values (406) 35677
57.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 61711
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
기 4915
 
8.0%
+ 4868
 
7.9%
구 3381
 
5.5%
장 2935
 
4.8%
동 2028
 
3.3%
운 2012
 
3.3%
리 1836
 
3.0%
1610
 
2.6%
1 1316
 
2.1%
체 1133
 
1.8%
Other values (406) 35677
57.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 61711
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
기 4915
 
8.0%
+ 4868
 
7.9%
구 3381
 
5.5%
장 2935
 
4.8%
동 2028
 
3.3%
운 2012
 
3.3%
리 1836
 
3.0%
1610
 
2.6%
1 1316
 
2.1%
체 1133
 
1.8%
Other values (406) 35677
57.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 61711
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
기 4915
 
8.0%
+ 4868
 
7.9%
구 3381
 
5.5%
장 2935
 
4.8%
동 2028
 
3.3%
운 2012
 
3.3%
리 1836
 
3.0%
1610
 
2.6%
1 1316
 
2.1%
체 1133
 
1.8%
Other values (406) 35677
57.8%

공원보유시설(유희시설)
Text

MISSING 

Distinct1351
Distinct (%)21.1%
Missing11152
Missing (%)63.5%
Memory size137.3 KiB
2024-08-14T01:00:28.880096image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length77
Median length60
Mean length9.7531192
Min length1

Characters and Unicode

Total characters62537
Distinct characters402
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique979 ?
Unique (%)15.3%

Sample

1st row조합놀이대
2nd row그네, 조합놀이대
3rd row조합놀이대
4th row흔들놀이기구, 조합놀이대
5th row조합놀이대+짚라인+개미터널
ValueCountFrequency (%)
조합놀이대 2057
25.5%
등 365
 
4.5%
어린이놀이터 291
 
3.6%
그네 278
 
3.5%
조합놀이대+그네 258
 
3.2%
조합놀이대1 218
 
2.7%
놀이터 192
 
2.4%
어린이놀이시설 190
 
2.4%
흔들놀이기구 151
 
1.9%
조합놀이대+흔들놀이기구 107
 
1.3%
Other values (1277) 3950
49.0%
2024-08-14T01:00:29.135515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 8145
13.0%
놀 7442
 
11.9%
대 5006
 
8.0%
+ 4898
 
7.8%
조 4888
 
7.8%
합 4878
 
7.8%
그 1875
 
3.0%
네 1864
 
3.0%
1647
 
2.6%
1 1554
 
2.5%
Other values (392) 20340
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 62537
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
이 8145
13.0%
놀 7442
 
11.9%
대 5006
 
8.0%
+ 4898
 
7.8%
조 4888
 
7.8%
합 4878
 
7.8%
그 1875
 
3.0%
네 1864
 
3.0%
1647
 
2.6%
1 1554
 
2.5%
Other values (392) 20340
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 62537
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
이 8145
13.0%
놀 7442
 
11.9%
대 5006
 
8.0%
+ 4898
 
7.8%
조 4888
 
7.8%
합 4878
 
7.8%
그 1875
 
3.0%
네 1864
 
3.0%
1647
 
2.6%
1 1554
 
2.5%
Other values (392) 20340
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 62537
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
이 8145
13.0%
놀 7442
 
11.9%
대 5006
 
8.0%
+ 4898
 
7.8%
조 4888
 
7.8%
합 4878
 
7.8%
그 1875
 
3.0%
네 1864
 
3.0%
1647
 
2.6%
1 1554
 
2.5%
Other values (392) 20340
32.5%

공원보유시설(편익시설)
Text

MISSING 

Distinct1388
Distinct (%)27.5%
Missing12511
Missing (%)71.2%
Memory size137.3 KiB
2024-08-14T01:00:29.323587image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length161
Median length82
Mean length7.9926776
Min length1

Characters and Unicode

Total characters40387
Distinct characters328
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1107 ?
Unique (%)21.9%

Sample

1st row화장실
2nd row화장실
3rd row파고라 1식
4th row파고라 1식
5th row파고라 1식
ValueCountFrequency (%)
화장실 1023
 
16.0%
파고라 437
 
6.8%
등 317
 
5.0%
음수대 228
 
3.6%
평의자 203
 
3.2%
벤치 157
 
2.5%
주차장+화장실 156
 
2.4%
주차장 127
 
2.0%
장의자 117
 
1.8%
정자+벤치 100
 
1.6%
Other values (1381) 3537
55.2%
2024-08-14T01:00:29.605809image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 4335
 
10.7%
장 2869
 
7.1%
자 2593
 
6.4%
실 2072
 
5.1%
화 2065
 
5.1%
의 1797
 
4.4%
라 1440
 
3.6%
파 1440
 
3.6%
고 1438
 
3.6%
1349
 
3.3%
Other values (318) 18989
47.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 40387
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
+ 4335
 
10.7%
장 2869
 
7.1%
자 2593
 
6.4%
실 2072
 
5.1%
화 2065
 
5.1%
의 1797
 
4.4%
라 1440
 
3.6%
파 1440
 
3.6%
고 1438
 
3.6%
1349
 
3.3%
Other values (318) 18989
47.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 40387
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
+ 4335
 
10.7%
장 2869
 
7.1%
자 2593
 
6.4%
실 2072
 
5.1%
화 2065
 
5.1%
의 1797
 
4.4%
라 1440
 
3.6%
파 1440
 
3.6%
고 1438
 
3.6%
1349
 
3.3%
Other values (318) 18989
47.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 40387
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
+ 4335
 
10.7%
장 2869
 
7.1%
자 2593
 
6.4%
실 2072
 
5.1%
화 2065
 
5.1%
의 1797
 
4.4%
라 1440
 
3.6%
파 1440
 
3.6%
고 1438
 
3.6%
1349
 
3.3%
Other values (318) 18989
47.0%

공원보유시설(교양시설)
Text

MISSING 

Distinct338
Distinct (%)53.5%
Missing16932
Missing (%)96.4%
Memory size137.3 KiB
2024-08-14T01:00:29.725908image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length77
Median length64
Mean length6.8370253
Min length1

Characters and Unicode

Total characters4321
Distinct characters316
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique294 ?
Unique (%)46.5%

Sample

1st row야외무대
2nd row야외무대
3rd row생태연못+데크관찰대
4th row관람녹지
5th row거석A+생태도랑+여울+거석B
ValueCountFrequency (%)
야외무대 83
 
11.0%
60
 
8.0%
도서관 34
 
4.5%
야외공연장 22
 
2.9%
미조성 16
 
2.1%
화장실 14
 
1.9%
경로당 12
 
1.6%
기념비 12
 
1.6%
공연장 10
 
1.3%
1개소 10
 
1.3%
Other values (367) 480
63.7%
2024-08-14T01:00:29.926759image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 238
 
5.5%
관 202
 
4.7%
야 169
 
3.9%
외 166
 
3.8%
대 141
 
3.3%
장 121
 
2.8%
무 121
 
2.8%
121
 
2.8%
공 91
 
2.1%
화 86
 
2.0%
Other values (306) 2865
66.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4321
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
+ 238
 
5.5%
관 202
 
4.7%
야 169
 
3.9%
외 166
 
3.8%
대 141
 
3.3%
장 121
 
2.8%
무 121
 
2.8%
121
 
2.8%
공 91
 
2.1%
화 86
 
2.0%
Other values (306) 2865
66.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4321
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
+ 238
 
5.5%
관 202
 
4.7%
야 169
 
3.9%
외 166
 
3.8%
대 141
 
3.3%
장 121
 
2.8%
무 121
 
2.8%
121
 
2.8%
공 91
 
2.1%
화 86
 
2.0%
Other values (306) 2865
66.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4321
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
+ 238
 
5.5%
관 202
 
4.7%
야 169
 
3.9%
외 166
 
3.8%
대 141
 
3.3%
장 121
 
2.8%
무 121
 
2.8%
121
 
2.8%
공 91
 
2.1%
화 86
 
2.0%
Other values (306) 2865
66.3%

공원보유시설(기타시설)
Text

MISSING 

Distinct1138
Distinct (%)41.9%
Missing14850
Missing (%)84.5%
Memory size137.3 KiB
2024-08-14T01:00:30.095169image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length159
Median length110
Mean length10.672439
Min length1

Characters and Unicode

Total characters28965
Distinct characters480
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique897 ?
Unique (%)33.1%

Sample

1st row우수관로+원형수로관+육가+집수정
2nd row우수관로+원형수로관+육가+집수정
3rd rowPvc이중벽관+원형수로관+집수정
4th rowPVC DC 엘보+U형플륨관 설치+압연강판+우수관로+장대석놓기+집수정설치(트렌치용+레미콘 관급)
5th row도복장PVC관+연결BOX관+우수관로+월류관+집수정
ValueCountFrequency (%)
등 262
 
6.8%
cctv 244
 
6.3%
파고라 144
 
3.7%
공원등 136
 
3.5%
조경시설,산책로 116
 
3.0%
의자 107
 
2.8%
안내판 98
 
2.5%
벤치 91
 
2.4%
88
 
2.3%
외 76
 
2.0%
Other values (1166) 2503
64.8%
2024-08-14T01:00:30.365175image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 2713
 
9.4%
1155
 
4.0%
수 1035
 
3.6%
자 937
 
3.2%
등 818
 
2.8%
) 746
 
2.6%
( 746
 
2.6%
C 681
 
2.4%
정 563
 
1.9%
의 547
 
1.9%
Other values (470) 19024
65.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 28965
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
+ 2713
 
9.4%
1155
 
4.0%
수 1035
 
3.6%
자 937
 
3.2%
등 818
 
2.8%
) 746
 
2.6%
( 746
 
2.6%
C 681
 
2.4%
정 563
 
1.9%
의 547
 
1.9%
Other values (470) 19024
65.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 28965
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
+ 2713
 
9.4%
1155
 
4.0%
수 1035
 
3.6%
자 937
 
3.2%
등 818
 
2.8%
) 746
 
2.6%
( 746
 
2.6%
C 681
 
2.4%
정 563
 
1.9%
의 547
 
1.9%
Other values (470) 19024
65.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 28965
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
+ 2713
 
9.4%
1155
 
4.0%
수 1035
 
3.6%
자 937
 
3.2%
등 818
 
2.8%
) 746
 
2.6%
( 746
 
2.6%
C 681
 
2.4%
정 563
 
1.9%
의 547
 
1.9%
Other values (470) 19024
65.7%

지정고시일
Date

MISSING 

Distinct3951
Distinct (%)27.5%
Missing3172
Missing (%)18.1%
Memory size137.3 KiB
Minimum1905-06-19 00:00:00
Maximum2023-11-10 00:00:00
2024-08-14T01:00:30.555478image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:30.642460image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관명
Text

MISSING 

Distinct314
Distinct (%)1.9%
Missing1029
Missing (%)5.9%
Memory size137.3 KiB
2024-08-14T01:00:30.848309image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length39
Median length27
Mean length11.134744
Min length3

Characters and Unicode

Total characters184113
Distinct characters211
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)0.3%

Sample

1st row경기도 양평군청
2nd row경기도 양평군청
3rd row경기도 양평군청
4th row경기도 양평군청
5th row경기도 양평군청
ValueCountFrequency (%)
경기도 3825
 
10.0%
충청남도 1724
 
4.5%
서울특별시 1533
 
4.0%
경상남도 1230
 
3.2%
경상북도 932
 
2.4%
전라남도 873
 
2.3%
충청북도 789
 
2.1%
공원관리과 745
 
2.0%
인천광역시 670
 
1.8%
공원녹지과 656
 
1.7%
Other values (330) 25225
66.0%
2024-08-14T01:00:31.129590image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21667
 
11.8%
청 16057
 
8.7%
시 15781
 
8.6%
도 11712
 
6.4%
구 6723
 
3.7%
경 6388
 
3.5%
원 5505
 
3.0%
남 4685
 
2.5%
광 4493
 
2.4%
기 3966
 
2.2%
Other values (201) 87136
47.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 184113
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
21667
 
11.8%
청 16057
 
8.7%
시 15781
 
8.6%
도 11712
 
6.4%
구 6723
 
3.7%
경 6388
 
3.5%
원 5505
 
3.0%
남 4685
 
2.5%
광 4493
 
2.4%
기 3966
 
2.2%
Other values (201) 87136
47.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 184113
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
21667
 
11.8%
청 16057
 
8.7%
시 15781
 
8.6%
도 11712
 
6.4%
구 6723
 
3.7%
경 6388
 
3.5%
원 5505
 
3.0%
남 4685
 
2.5%
광 4493
 
2.4%
기 3966
 
2.2%
Other values (201) 87136
47.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 184113
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
21667
 
11.8%
청 16057
 
8.7%
시 15781
 
8.6%
도 11712
 
6.4%
구 6723
 
3.7%
경 6388
 
3.5%
원 5505
 
3.0%
남 4685
 
2.5%
광 4493
 
2.4%
기 3966
 
2.2%
Other values (201) 87136
47.3%

전화번호
Text

MISSING 

Distinct566
Distinct (%)3.4%
Missing1125
Missing (%)6.4%
Memory size137.3 KiB
2024-08-14T01:00:31.271559image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.082365
Min length9

Characters and Unicode

Total characters198622
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)0.8%

Sample

1st row031-770-2358
2nd row031-770-2358
3rd row031-770-2358
4th row031-770-2358
5th row031-770-2358
ValueCountFrequency (%)
031-8024-4248 538
 
3.3%
031-5189-6961 339
 
2.1%
031-5189-6626 253
 
1.5%
063-281-2689 249
 
1.5%
064-728-3601 195
 
1.2%
031-940-8710 173
 
1.1%
041-521-2723 169
 
1.0%
054-270-5735 168
 
1.0%
061-659-4627 161
 
1.0%
041-350-4212 159
 
1.0%
Other values (556) 14035
85.4%
2024-08-14T01:00:31.516987image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 32877
16.6%
0 28923
14.6%
2 20387
10.3%
3 20048
10.1%
4 17725
8.9%
5 17440
8.8%
1 17111
8.6%
6 15515
7.8%
8 11548
 
5.8%
7 9142
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 198622
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 32877
16.6%
0 28923
14.6%
2 20387
10.3%
3 20048
10.1%
4 17725
8.9%
5 17440
8.8%
1 17111
8.6%
6 15515
7.8%
8 11548
 
5.8%
7 9142
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 198622
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 32877
16.6%
0 28923
14.6%
2 20387
10.3%
3 20048
10.1%
4 17725
8.9%
5 17440
8.8%
1 17111
8.6%
6 15515
7.8%
8 11548
 
5.8%
7 9142
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 198622
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 32877
16.6%
0 28923
14.6%
2 20387
10.3%
3 20048
10.1%
4 17725
8.9%
5 17440
8.8%
1 17111
8.6%
6 15515
7.8%
8 11548
 
5.8%
7 9142
 
4.6%

데이터기준일자
Date

Distinct170
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size137.3 KiB
Minimum2019-01-01 00:00:00
Maximum2024-07-26 00:00:00
2024-08-14T01:00:31.625627image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:31.718702image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Text

Distinct233
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:31.920497image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters122948
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row4170000
2nd row4170000
3rd row4170000
4th row4170000
5th row4170000
ValueCountFrequency (%)
6440000 953
 
5.4%
5530000 592
 
3.4%
3910000 538
 
3.1%
5670000 469
 
2.7%
5710000 433
 
2.5%
3740000 335
 
1.9%
4050000 279
 
1.6%
3940000 253
 
1.4%
4641000 249
 
1.4%
5350000 224
 
1.3%
Other values (223) 13239
75.4%
2024-08-14T01:00:32.203251image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72423
58.9%
3 11524
 
9.4%
4 9592
 
7.8%
5 7424
 
6.0%
1 5014
 
4.1%
6 4914
 
4.0%
9 3330
 
2.7%
7 2997
 
2.4%
8 2862
 
2.3%
2 2800
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 122948
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 72423
58.9%
3 11524
 
9.4%
4 9592
 
7.8%
5 7424
 
6.0%
1 5014
 
4.1%
6 4914
 
4.0%
9 3330
 
2.7%
7 2997
 
2.4%
8 2862
 
2.3%
2 2800
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 122948
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 72423
58.9%
3 11524
 
9.4%
4 9592
 
7.8%
5 7424
 
6.0%
1 5014
 
4.1%
6 4914
 
4.0%
9 3330
 
2.7%
7 2997
 
2.4%
8 2862
 
2.3%
2 2800
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 122948
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 72423
58.9%
3 11524
 
9.4%
4 9592
 
7.8%
5 7424
 
6.0%
1 5014
 
4.1%
6 4914
 
4.0%
9 3330
 
2.7%
7 2997
 
2.4%
8 2862
 
2.3%
2 2800
 
2.3%

제공기관명
Text

Distinct233
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size137.3 KiB
2024-08-14T01:00:32.446473image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.0192439
Min length4

Characters and Unicode

Total characters140850
Distinct characters139
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row경기도 양평군
2nd row경기도 양평군
3rd row경기도 양평군
4th row경기도 양평군
5th row경기도 양평군
ValueCountFrequency (%)
경기도 4519
 
13.4%
서울특별시 1951
 
5.8%
충청남도 1726
 
5.1%
경상남도 1242
 
3.7%
전라남도 1040
 
3.1%
경상북도 1006
 
3.0%
충청북도 789
 
2.3%
인천광역시 735
 
2.2%
부산광역시 664
 
2.0%
전북특별자치도 658
 
1.9%
Other values (214) 19505
57.6%
2024-08-14T01:00:32.727666image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16271
 
11.6%
시 15251
 
10.8%
도 12031
 
8.5%
경 6970
 
4.9%
구 6012
 
4.3%
남 4998
 
3.5%
기 4659
 
3.3%
광 4604
 
3.3%
특 3669
 
2.6%
별 3669
 
2.6%
Other values (129) 62716
44.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 140850
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
16271
 
11.6%
시 15251
 
10.8%
도 12031
 
8.5%
경 6970
 
4.9%
구 6012
 
4.3%
남 4998
 
3.5%
기 4659
 
3.3%
광 4604
 
3.3%
특 3669
 
2.6%
별 3669
 
2.6%
Other values (129) 62716
44.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 140850
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
16271
 
11.6%
시 15251
 
10.8%
도 12031
 
8.5%
경 6970
 
4.9%
구 6012
 
4.3%
남 4998
 
3.5%
기 4659
 
3.3%
광 4604
 
3.3%
특 3669
 
2.6%
별 3669
 
2.6%
Other values (129) 62716
44.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 140850
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
16271
 
11.6%
시 15251
 
10.8%
도 12031
 
8.5%
경 6970
 
4.9%
구 6012
 
4.3%
남 4998
 
3.5%
기 4659
 
3.3%
광 4604
 
3.3%
특 3669
 
2.6%
별 3669
 
2.6%
Other values (129) 62716
44.5%

Interactions

2024-08-14T01:00:24.830402image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.290447image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.588197image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.897331image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.366000image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.658936image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.962230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.467021image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-08-14T01:00:24.768051image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-08-14T01:00:32.786123image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
경도공원구분공원면적위도
경도1.0000.062-0.027-0.352
공원구분0.0621.0000.0660.072
공원면적-0.0270.0661.000-0.044
위도-0.3520.072-0.0441.000

Missing values

2024-08-14T01:00:25.121366image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-08-14T01:00:25.348506image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-08-14T01:00:25.558984image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관리번호공원명공원구분소재지도로명주소소재지지번주소위도경도공원면적공원보유시설(운동시설)공원보유시설(유희시설)공원보유시설(편익시설)공원보유시설(교양시설)공원보유시설(기타시설)지정고시일관리기관명전화번호데이터기준일자제공기관코드제공기관명
041830-00017광탄2호 소공원소공원NaN경기도 양평군 용문면 광탄리 71137.509628127.628406856.0NaNNaNNaNNaNNaN1994-02-25경기도 양평군청031-770-23582023-05-264170000경기도 양평군
141830-00031광탄3호 소공원소공원NaN경기도 양평군 용문면 광탄리 76237.508443127.627414847.0NaNNaNNaNNaNNaN1994-02-25경기도 양평군청031-770-23582023-05-264170000경기도 양평군
241830-00018공흥 소공원소공원NaN경기도 양평군 양평읍 공흥리 885-137.493844127.5093261276.0NaNNaNNaNNaNNaN2012-11-22경기도 양평군청031-770-23582023-05-264170000경기도 양평군
341830-00019한강아트로드 공원소공원NaN경기도 양평군 강하면 운심리 43-2537.496021127.4082163300.0NaNNaNNaNNaNNaN2012-08-30경기도 양평군청031-770-23582023-05-264170000경기도 양평군
441830-00020강하 소공원소공원경기도 양평군 강하면 운심길 58경기도 양평군 강하면 운심리 28-137.496164127.412326394.0농구장+축구장+테니스장NaNNaNNaNNaN2012-08-30경기도 양평군청031-770-23582023-05-264170000경기도 양평군
541830-00021오빈12호 소공원소공원NaN경기도 양평군 양평읍 오빈리 96-4037.505413127.476939864.0NaNNaNNaNNaNNaN2013-10-15경기도 양평군청031-770-23582023-05-264170000경기도 양평군
641830-00022오빈13호 소공원소공원NaN경기도 양평군 양평읍 오빈리 88-4737.506925127.479025568.0NaNNaNNaNNaNNaN2013-10-15경기도 양평군청031-770-23582023-05-264170000경기도 양평군
741830-00023오빈14호 소공원소공원경기도 양평군 양평읍 오빈1리길12번길 4경기도 양평군 양평읍 오빈리 88-4637.507148127.479103404.0NaNNaNNaNNaNNaN2013-10-15경기도 양평군청031-770-23582023-05-264170000경기도 양평군
841830-00024오빈15호 소공원소공원경기도 양평군 양평읍 오빈1리길 9경기도 양평군 양평읍 오빈리 81-3237.506986127.479677293.0NaNNaNNaNNaNNaN2013-10-15경기도 양평군청031-770-23582023-05-264170000경기도 양평군
941830-00025양근소공원(17호)소공원NaN경기도 양평군 양평읍 양근리 53-237.499467127.4921822037.0NaNNaNNaNNaNNaN2014-05-26경기도 양평군청031-770-23582023-05-264170000경기도 양평군
관리번호공원명공원구분소재지도로명주소소재지지번주소위도경도공원면적공원보유시설(운동시설)공원보유시설(유희시설)공원보유시설(편익시설)공원보유시설(교양시설)공원보유시설(기타시설)지정고시일관리기관명전화번호데이터기준일자제공기관코드제공기관명
1755427260-00018희망공원어린이공원대구광역시 수성구 들안로 13길 118대구광역시 수성구 상동 1735.839283128.6151492655.0NaN조합놀이대NaNNaNNaN1976-07-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
1755527260-00019청소년공원어린이공원대구광역시 수성구 수성로 32길 99대구광역시 수성구 상동 5435.836736128.6134592648.0배드민턴장NaNNaNNaNNaN2009-03-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
1755627260-00020들안길공원어린이공원NaN대구광역시 수성구 상동 34335.834005128.6134712644.0NaN조합놀이대NaNNaNNaN1976-07-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
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1755827260-00022샛터공원어린이공원NaN대구광역시 수성구 두산동 4135.837827128.6209932633.0NaN조합놀이대NaNNaNNaN1976-07-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
1755927260-00023아랫마을공원어린이공원대구광역시 수성구 들안로 8길 68-5대구광역시 수성구 두산동 14135.834179128.6196662642.0NaN조합놀이대NaNNaNNaN1976-07-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
1756027260-00024끝동공원어린이공원NaN대구광역시 수성구 두산동 15535.832236128.6182092654.0NaN조합놀이대NaNNaNNaN1976-07-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
1756127260-00025지산공원어린이공원NaN대구광역시 수성구 지산동 101335.834941128.6269453315.0NaN조합놀이대NaNNaNNaN1976-07-30대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
1756227260-00026현대공원어린이공원NaN대구광역시 수성구 지산동 1184-535.822580128.6253162237.0NaN조합놀이대NaNNaNNaN2003-08-13대구광역시 수성구청053-666-28622024-07-113460000대구광역시 수성구
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